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Research Articles

Hypoglycemic and hepatoprotective effects in adult zebrafish (Danio rerio) of fisetinidol isolated from Bauhinia pentandra: In vivo and in silico assays

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Pages 2274-2288 | Received 07 Oct 2021, Accepted 08 Jan 2022, Published online: 22 Jan 2022
 

Abstract

Diabetes mellitus is a chronic metabolic disorder that has been increasing drastically around the worldwide. It is important to emphasize that although many drugs are commercially available to treat diabetes, many of them have shown a number of adverse effects. Therefore, search for new antidiabetic agents is of great interest, and natural products, especially those obtained from plants sources, may be an alternative to available drugs. This study reports the in vivo and in silico evaluation of the hypoglycemic activity of fisetinidol. The conformational analysis confirmed that the fisetinidol compound possesses two valleys in the potential energy curve, showing a stable conformer on the global minimum of the PES defined by the dihedral angle θ (C6-C7-O-H) at 179.9°, whose energy is equal to zero. In addition, fisetinidol has shown promise in glycemic control and oxidative stress caused by hyperglycemia induced by high sucrose concentration, causing hypoglycemic and hepatoprotective effects in adult zebrafish. ADMET studies showed that fisetinidol has high passive permeability, low clearance and low toxic risk by ingestion, and computational studies demonstrated that fisetinidol complexes in the same region as metformin and α-acarbose, which constitutes a strong indication that fisetinidol has the same inhibitory mechanisms of α-acarbose and metformin.

Communicated by Ramaswamy H. Sarma.

Acknowledgments

We thank CENAPAD-SP for the use of the Gaussian09 software package and for computational facilities made available through the project “proj373”.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Financial support from FUNCAP and CNPq is also acknowledged. H.S. Santos acknowledges financial support from the PQ/FUNCAP (Grant#: BP4-0172-00075.01.00/20). A.M.R. Teixeira, Ph.D, also acknowledges financial support from the PQ/CNPq (Grant#: 303963/2015-8). We acknowledge Centro Nacional de Processamento de Alto Desempenho (CENAPAD) of the Federal University of Ceará (UFC) for the use of the Gaussian09 software package. F.W.Q. Almeida-Neto thanks CNPq for his grant.

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